As wireless communication systems such as cellular telephone, satellite, and microwave communication systems become widely deployed and continue to attract a growing number of users, there is a pressing need to accommodate a large and variable number of communication devices transmitting a growing volume of data over wide cellular areas with fixed resources. Traditional communication system designs have become challenged to provide reliable communication over a reasonably wide geographical area in view of the general need to limit transmitter power and bandwidth for the rapidly growing customer base and expanding levels of service.
The Third Generation Partnership Project Long Term Evolution (“3GPP LTE”) project is the name generally used to describe an ongoing effort across the industry to improve the universal mobile telecommunications system (“UMTS”) for mobile communication to cope with continuing new requirements and the growing base of users. The goals of this broadly based project include improving communication efficiency, lowering costs, improving services, making use of new spectrum opportunities, and achieving better integration with other open standards. The 3GPP LTE project is not by itself a standard-generating effort, but will result in new recommendations for standards for the UMTS.
In wireless communication systems such as 3GPP LTE cellular communication systems, it is necessary to store data associated with one or more received messages in so-called soft buffer memory that stores the so-called soft information associated with received bits, which is also referred to as soft bits. The soft information for a received bit contains not only the most likely value of the bit, but also a measure of its reliability (e.g., an estimate of the received signal energy relative to a noise level). The term “soft information” or “soft bit” generally refers to not making a hard decision about the value of a bit during demodulation and/or input to a decoder, which is also referred to as a soft decision. These measures of reliability can be used to enhance decoding performance. For example, a decoded received packet and its supporting data (i.e., soft bits) are generally stored in soft buffer memory to accommodate combining the data with retransmitted data in the event that a determination is made that the packet was received in error for a previous transmission or previous retransmission. A hybrid automatic retransmit request (“HARQ”) signal requests that the data be retransmitted so that retransmitted data can be combined in the receiver with the originally received packet.
Multiple-input/multiple-output (“MIMO”) refers to techniques in wireless communications systems wherein multiple transmit and receive antennas in combination with detectors in a receiver provide time and spatial diversity and spatial multiplexing for a signal reception process. These techniques provide significant enhancements for signals that are ordinarily degraded due to fading (e.g., as a result of multiple paths with unequal transit delays that may exist between a transmitter and a receiver). Furthermore, MIMO allows multiplexing of data on different spatial streams, so called spatial multiplexing, and thus allows in principle an increase in the data rate n-fold if n antennas are deployed at both transmitter and receiver by transmitting n streams concurrently. These concurrent streams are also called MIMO codewords.
The digital structures, particularly in a receiver, that enable HARQ and MIMO processes and their supporting mechanisms require a substantial amount of soft buffer memory for temporary data storage, particularly in the higher-level categories of user equipment that are configured to support multiple concurrent transmission and reception activities. The amount of soft buffer memory that can be required can be substantially greater than a megabyte. Thus, a practical need arises in the design of a wireless transceiver such as a user equipment (“UE”) to allocate soft buffer memory between HARQ and MIMO processes.
While it has been contemplated that HARQ memory be partitioned unequally between HARQ processes, some proponents would prefer to provide an equal partition of HARQ memory. The detriment, however, is that equal partitioning of memory offers no hardware advantage, but instead increases UE cost by requiring more HARQ memory than is necessary. The UE memory for HARQ can be quite large, and accordingly substantially influences memory partitioning. It has also been proposed to retain the ability to configure HARQ memory per process, in addition to limited buffer rate matching (“LBRM”), in order to minimize UE memory requirements. Additionally, it is possible to split the soft buffer memory asymmetrically per MIMO codeword (i.e., each MIMO codeword would be associated with a HARQ process). It has also been noted that in view of the small coded payloads associated with voice over internet protocol (“VoIP”) in comparison to internet protocol (“IP”) packets, that non-equal memory for each HARQ process, independent of the use of LBRM, might be used to minimize overall memory requirements.
Considering the limitations and various conflicting system design directions as described above, a system and method to provide a practical allocation of soft buffer memory between HARQ and MIMO processes is not presently available for the wireless applications that lie ahead. Accordingly, what is needed in the art is a communication system that operates with a practical allocation of soft buffer memory for HARQ and MIMO processes in the operating environments that can be anticipated to be encountered.